Gen AI research poster exhibition

Tirth Kanani of the University of Birmingham shows an attendee a poster for “GraphMinds” (credit: Michelle McGrath)

Attendees viewing the poster exhibition at the Gen AI Hub Launch (credit: Michelle McGrath)

A poster exhibitor discussing their research with Hub Investigator, Professor Jack Stilgoe of UCL (credit: Michelle McGrath)

Last week’s Launch Event was an opportunity for students, researchers and entrepreneurs to present their ideas and research on Generative AI to a wider audience.

Exhibitors included students and researchers from Hub partner institutions, other universities and the AI hubs AIchemy, APRIL and Informed AI. Here is the full list of participants:

• Bríd-Áine Parnell: University of Edinburgh - Narratives of Power in AI Policy

• Santhosh Sivasubramani: APRIL Hub, University of Edinburgh - Generative AI as a Catalyst for Beyond-CMOS Semiconductor Technologies: A Strategic Roadmap from APRIL

• Weihao Xia: University College London - UMBRAE: Unified Multimodal Brain Decoding

• Mingtian Zhang: University College London / Vectify AI - Improving Probabilistic Diffusion Models With Optimal Diagonal Covariance Matching Towards Training One-Step Diffusion Models Without Distillation

• Simon Ellershaw: University College London: Foresight-SDE: a national-scale foundation model of 51 million patients for generative medical event prediction

• Zixing Song: University of Cambridge - Domain-Adapted Diffusion Model for PROTAC Linker Design Through the Lens of Density Ratio in Chemical Space

• Tirth Bharatbhai Kanani: University of Birmingham - GraphMinds: Leveraging Large Language Models and Knowledge Graphs for Transparent and Efficient AI Systems

• Dar-Yen Chen: Centre for Vision, Speech and Signal Processing (CVSSP), University of Surrey - NitroFusion: High-Fidelity Single-Step Diffusion through Dynamic Adversarial Training

• Haohe Liu: University of Surrey - Diffusion models for audio

• William Morgans: University of Manchester - ord-timeVAE learns latent embeddings in coarsely labelled biological timecourses

• Kevin Huang: Gatsby Unit, University College London - Diagonal Symmetrization of Neural Network Solvers for the Many-Electron Schrödinger Equation

• Sid Jaggi: Informed AI Hub, University of Bristol - General Hub information poster

• Chris Mellor: Alchemy Hub, Imperial College London - General Hub information poster

• Hugh Dance: Gatsby Unit, University College London - Efficiently Vectorized MCMC on Modern Accelerators

• Kenneth Harris: University College London - A simple workflow for LLM-assisted scientific data analysis

To find out more about the exhibition, please email the Hub.

Photography by Michelle McGrath